|Date: ||Thu, 23 Nov 2006 11:13:35 -0800|
|Reply-To: ||"Dennis G. Fisher, Ph.D." <dfisher@CSULB.EDU>|
|Sender: ||"SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>|
|From: ||"Dennis G. Fisher, Ph.D." <dfisher@CSULB.EDU>|
|Subject: ||Re: logistic versus discriminant?|
|Content-Type: ||text/plain; charset=ISO-8859-1; format=flowed|
I was able to figure out which article he was referring to. It is the
Lei, P. W., & Koehly, L. M. (2003). Linear discriminant analysis versus
logistic regression: A comparison of classification errors in the
two-group case. The Journal of Experimental Education, 71(1), 25-49.
I was able to get it online through another database. Thanks.
David L Cassell wrote:
> bnz6@CDC.GOV replied:
>> There is a nice article that summarizes previous research in this area.
>> You can access it here:
>> I hope this helps.
>> Mark J. Lamias
>> SAIC Statistical Consultant
>> Office of Informatics
>> National Center for Preparedness, Detection, and Control of Infectious
>> Coordinating Center for Infectious Diseases
>> US Centers for Disease Control and Prevention
>> w: (404) 639-6707
>> m: (404) 543-1394
>> -----Original Message-----
>> From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of
>> Dennis G. Fisher, Ph.D.
>> Sent: Tuesday, November 21, 2006 12:03 PM
>> To: SAS-L@LISTSERV.UGA.EDU
>> Subject: logistic versus discriminant?
>> I am working on a proposal and one of my collaborators is making the
>> claim that if the predictor variables are normally distributed,
>> continuous etc. then it is better to use discriminant function analysis
>> because it has more power. I have never heard this before and am
>> wondering if it is true and what citations would back up this claim. I
>> am also having some difficulty understanding what power means in this
>> comparison. TIA
>> Dennis Fisher
> Unfortunately, you may not be able to get to that URL. It
> requires specific access rights.
> David L. Cassell
> mathematical statistician
> Design Pathways
> 3115 NW Norwood Pl.
> Corvallis OR 97330
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